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Record W3118923821 · doi:10.3390/molecules26010189

Iron Chelation in Local Infection

2021· review· en· W3118923821 on OpenAlexaff
Cassidy Scott, Gaurav Arora, Kayle Dickson, Christine Lehmann

Bibliographic record

VenueMolecules · 2021
Typereview
Languageen
FieldMedicine
TopicIron Metabolism and Disorders
Canadian institutionsDalhousie University
Fundersnot available
KeywordsChelationReactive oxygen speciesInnate immune systemImmune systemIron supplementationImmunologyMicrobiologyBiologyIron deficiencyChemistryMedicineCell biologyInternal medicine

Abstract

fetched live from OpenAlex

Iron is an essential element in multiple biochemical pathways in humans and pathogens. As part of the innate immune response in local infection, iron availability is restricted locally in order to reduce overproduction of reactive oxygen species by the host and to attenuate bacterial growth. This physiological regulation represents the rationale for the therapeutic use of iron chelators to support induced iron deprivation and to treat infections. In this review paper we discuss the importance of iron regulation through examples of local infection and the potential of iron chelation in treating infection.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.994
Threshold uncertainty score0.625

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.027
GPT teacher head0.334
Teacher spread0.307 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations37
Published2021
Admission routes1
Has abstractyes

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